Deep-learning framework designed to fulfill medical imaging analysis : segmentation / classification / generation / harmonization
Python 99.27%Shell 0.73%
dl_generic's Introduction
DL-Generic : Internal project at Grenoble Institut of Neuroscience
Barbier Team
Developed by Stenzel Cackowski
Installation:
pip3 install virtualenv
virtualenv env
source env/bin/activate
sudo pip3 install -r requirements.txt
Usage
First dispatch your data in a container folder "$data" in 3 folder "$train" "$val" "$test", using the BIDS nomenclature $data/$train/$subject_id/${subject_id}_${sequences_name}.nii.gz
Then generate patches to feed our neural network using the patches_generation.py script. --help will list required or optional additional parameters
Then you can generate and train you model using the "use_model.py" script. --help will list required or optional additional parameters
In case of generation / segmentation usage you might need to reconstruct infered output using the reconstruction.py script